Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article reports on the use of Commercial-Off-The-Shelf (COTS) software for developing a dynamic environment for an online public access catalogue (OPAC). COTS products are widely used throughout the industry. While there are many potential benefits, use of COTS components is also fraught with pitfalls. The research on creating a dynamic environment for OPACs is based on the previous work in this area, Public Access Catalogue Extension (PACE), which was developed with custom-based software programs. Although in the previous research project all the programs were successfully developed in C and C++, the present project relied very little on original and custom programming. Instead, a number of COTS products were used to construct the dynamic environment: Macromedia Director, 3D Dreams, Extreme 3D, Crossroads, and Easybase. These COTS products were chosen for their ability to produce the desired results, their availability at reasonable costs, and their capability to integrate with one another. A small experimental database with one hundred MARC records was constructed in Easybase. Models were built in Extreme 3D and converted to 3D Studio using Crossroads. These models were used in 3D Dreams to create three-dimensional environments for use in Macromedia Director.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.012 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it